Learning outcome

After completing the course, the student should be able to:* Understand the nature of dependency in clustered and repeated measurements, and how this dependency alters the approach to statistical analysis and modeling; as well as the consequences of not taking this information into account.

* Understand the principles of experimental design in which experimental factors vary both between and within clusters.

* Perform simple, descriptive analyses such as obtaining sample covariance and correlation, and corresponding graphical plots such as scatter plots, to illuminate key features of data with clustered and/or repeated observations.